P1-06-17: A New Pathological Response Index (PRI) for Neoadjuvant Chemotherapy Accurately Predicts Clinical Outcomes of Locally Advanced Breast Cancers (LAPBC).
Bibliographic record
Abstract
Abstract Pathological complete response (pCR) after neoadjuvant chemotherapy predicts overall survival that is independent of treatment regimen. However; pCR is not a perfect surrogate for overall survival, given that a significant number of patients who did not achieve pCR also have a good prognosis and a small number of patients with pCR still develop recurrences. Furthermore, residual cancer cells after neoadjuvant therapy includes a wide range of responses from near pCR to complete resistance. In this study we performed a comprehensive pathological assessment for 245 surgical specimens of LAPBC, treated at a single institution, removed after receiving neoadjuvant anthracycline combination chemotherapy only (n=152) or with Taxane (n=93) with median follow up 42 months. Progression free survival (PFS) was used as the study endpoint. For comparison, residual cancer burden (RCB) was calculated using web calculator at www.mdanderson,org/breast_BCR. A multivariate Cox regression model revealed that size of the residual invasive carcinoma (OR; 3.2, CI 95%; 1.6−6.1, p=0.001), presence of lympho-vascular invasion (OR; 2.4, CI 95%; 1.3−4.3, p=0.004), absence of any pathological evidence of response at the site of the primary tumour or axillary lymph nodes after CT (OR; 3.2, CI 95%; 2.2−8.0, p=0.00001), and presence of at least one apical lymph node metastases (OR; 4.2, CI 95%; 1.5−6.8, p=0.003) at surgery were significantly associated with shorter PFS. These results were used to develop a pathological response index (PRI) from which 5 prognostic subgroups with distinct clinical outcomes were identified. Patients with PRI-PG1 (n=110; 49%) had a good clinical outcomes in both ER+ (3-year PFS; 91%) and ER- tumours (3-year PFS; 84%). Moreover, patients with PRI-PGI who did not show pCR (n=69) had equivalent overall and PFS as those with PRI-PG1 who achieved pCR (n=41); p=NS. Patients with PRI-PG2-5, had a 5 fold increase in the risk of progression compared to those with PRI-PG1 (HR; 5.2, CI 95%; 2.9−9.6, p≤0.0001). ER+ patients with PRI-PG3-5 (25% of ER+ cases) had shorter 3-year PFS 30%) compared to those ER+ with PRI PG1-2 (91%) despite treatment with adjuvant hormonal therapy (HR=6.5, CI 95%; 2.8−14.7, p<0.0001). Similarly, HER2 positive patients with PRI- PG3-5 (20% of HER2+ patients) showed very rapid progression within < 3 years (PFS; 10%) vs. those with PRI-PG1-2 (PFS; 82%) despite trastuzumab treatment (HR=8.4; CI 95%; 2.8−25.0, p<0.0001). In conclusion, a pathological response index including size of residual tumour, post chemotherapy lymph node pathological stage, lympho-vascular invasion and any evidence of fibrotic/response reaction following neoadjuvant chemotherapy may accurately predict the chance of disease progression, identify a greater proportion of patients (>twice as many as pCR) who could potentially benefit from the neoadjuvant chemotherapy and may be able to spared further adjuvant therapy. Furthermore this new PRI may help to improve the sensitivity of pathological response as a study end-point for predicting tumours response to a given neoadjuvant regimen and enable biological markers to be studied in a good prognostic group in additional to pCR. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P1-06-17.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".